ash_model.measures.average_group_degree¶

ash_model.measures.average_group_degree(h, tid, hyperedge_size=None)[source]¶

Computes the average degree of each group (nodes having the same label in the attribute)

Parameters:

h (ASH) – ASH instance
tid (int) – the temporal id
hyperedge_size (int | None) – Specify the size of the hyperedges

Returns:

A dictionary with attribute names as keys and a dictionary of average degrees for each attribute value

Return type:

object

Examples

Average degree by color at tid=0 with the dataset above:

>>> import numpy as np, networkx as nx
>>> from ash_model.utils.networkx import from_networkx_maximal_cliques_list
>>> Gs = [nx.barabasi_albert_graph(100, 3, seed=i) for i in range(10)]
>>> rng = np.random.default_rng(42)
>>> for G in Gs:
...     for n in G.nodes():
...         G.nodes[n]['color'] = 'red' if rng.integers(0, 2) == 0 else 'blue'
>>> h = from_networkx_maximal_cliques_list(Gs)
>>> average_group_degree(h, tid=0)
{'color': {'red': 4.854166666666667, 'blue': 5.0}}